Scenario understanding and motion prediction for autonomous vehicles—review and comparison
Scenario understanding and motion prediction are essential components for completely
replacing human drivers and for enabling highly and fully automated driving (SAE-Level …
replacing human drivers and for enabling highly and fully automated driving (SAE-Level …
Evolvegraph: Multi-agent trajectory prediction with dynamic relational reasoning
Multi-agent interacting systems are prevalent in the world, from purely physical systems to
complicated social dynamic systems. In many applications, effective understanding of the …
complicated social dynamic systems. In many applications, effective understanding of the …
Conditional generative neural system for probabilistic trajectory prediction
J Li, H Ma, M Tomizuka - 2019 IEEE/RSJ International …, 2019 - ieeexplore.ieee.org
Effective understanding of the environment and accurate trajectory prediction of surrounding
dynamic obstacles are critical for intelligent systems such as autonomous vehicles and …
dynamic obstacles are critical for intelligent systems such as autonomous vehicles and …
Pip: Planning-informed trajectory prediction for autonomous driving
It is critical to predict the motion of surrounding vehicles for self-driving planning, especially
in a socially compliant and flexible way. However, future prediction is challenging due to the …
in a socially compliant and flexible way. However, future prediction is challenging due to the …
Spatio-temporal graph dual-attention network for multi-agent prediction and tracking
An effective understanding of the environment and accurate trajectory prediction of
surrounding dynamic obstacles are indispensable for intelligent mobile systems (eg …
surrounding dynamic obstacles are indispensable for intelligent mobile systems (eg …
Spectral temporal graph neural network for trajectory prediction
An effective understanding of the contextual environment and accurate motion forecasting of
surrounding agents is crucial for the development of autonomous vehicles and social mobile …
surrounding agents is crucial for the development of autonomous vehicles and social mobile …
Probabilistic prediction of interactive driving behavior via hierarchical inverse reinforcement learning
Autonomous vehicles (AVs) are on the road. To safely and efficiently interact with other road
participants, AVs have to accurately predict the behavior of surrounding vehicles and plan …
participants, AVs have to accurately predict the behavior of surrounding vehicles and plan …
Social-wagdat: Interaction-aware trajectory prediction via wasserstein graph double-attention network
Effective understanding of the environment and accurate trajectory prediction of surrounding
dynamic obstacles are indispensable for intelligent mobile systems (like autonomous …
dynamic obstacles are indispensable for intelligent mobile systems (like autonomous …
Interaction-aware multi-agent tracking and probabilistic behavior prediction via adversarial learning
J Li, H Ma, M Tomizuka - 2019 international conference on …, 2019 - ieeexplore.ieee.org
In order to enable high-quality decision making and motion planning of intelligent systems
such as robotics and autonomous vehicles, accurate probabilistic predictions for …
such as robotics and autonomous vehicles, accurate probabilistic predictions for …
Generic tracking and probabilistic prediction framework and its application in autonomous driving
Accurately tracking and predicting behaviors of surrounding objects are key prerequisites for
intelligent systems such as autonomous vehicles to achieve safe and high-quality decision …
intelligent systems such as autonomous vehicles to achieve safe and high-quality decision …